Moving 6-year analysis of Water_body_dissolved_oxygen_concentration in the Mediterranean Sea for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centered average of the season. 6-years periods span from 1971-1976 until 2014-2019. Observational data span from 1960 to 2019. Depth range (IODE standard depths): 2000.0, 1750.0, 1500.0, 1400.0, 1300.0, 1200.0, -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0, -30.0, -20.0, -10.0, -5.0, -0.0. Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. Profiles were interpolated at standard depths using weighted parabolic interpolation algorithm (Reiniger and Ross, 1968). GEBCO 1min topography is used for the contouring preparation. Analysed filed masked using relative error threshold 0.3 and 0.5. DIVA settings: A constant value for signal-to-noise ratio was used equal to 1. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. 'log(data)-exp(analysis' transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. Detrending of data: no. Advection constraint applied: no. Units: umol/l. The entire set of related maps can be found in the viewing service: http://ec.oceanbrowser.net/emodnet/ . Originators of Italian data sets-List of contributors: - Brunetti Fabio (OGS) - Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306 - Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987 - Cataletto Bruno (OGS) - Cinzia Comici Cinzia (OGS) - Civitarese Giuseppe (OGS) - DeVittor Cinzia (OGS) - Giani Michele (OGS) - Kovacevic Vedrana (OGS) - Mosetti Renzo (OGS) - Solidoro C.,Beran A.,Cataletto B.,Celussi M.,Cibic T.,Comici C.,Del Negro P.,De Vittor C.,Minocci M.,Monti M.,Fabbro C.,Falconi C.,Franzo A.,Libralato S.,Lipizer M.,Negussanti J.S.,Russel H.,Valli G., doi:10.6092/e5518899-b914-43b0-8139-023718aa63f5 - Celio Massimo (ARPA FVG) - Malaguti Antonella (ENEA) - Fonda Umani Serena (UNITS) - Bignami Francesco (ISAC/CNR) - Boldrini Alfredo (ISMAR/CNR) - Marini Mauro (ISMAR/CNR) - Miserocchi Stefano (ISMAR/CNR) - Zaccone Renata (IAMC/CNR) - Lavezza, R., Dubroca, L. F. C., Ludicone, D., Kress, N., Herut, B., Civitarese, G., Cruzado, A., Lefèvre, D., Souvermezoglou, E., Yilmaz, A., Tugrul, S., and Ribera d'Alcala, M.: Compilation of quality controlled nutrient profiles from the Mediterranean Sea, doi:10.1594/PANGAEA.771907, 2011.

This map presents all layers corresponding to "Retail sale of fish, crustaceans and molluscs in specialised stores" activities in the Atlantic area. For more information about this NACE code : https://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=DSP_NOM_DTL_VIEW&StrNom=NACE_REV2&StrLanguageCode=EN&IntPcKey=18511064&IntKey=18511154&StrLayoutCode=HIERARCHIC&IntCurrentPage=1 Indicators collected are : Business indicators per country

Seasonal Climatology of Silicate for Loire River for the period 1965-2019 and for the following seasons: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December Observational data span from 1965 to 2019. Depth levels (m): -125.0, -100.0, -75.0, -50.0,-40.0, -30.0, -25.0, -20.0, -15.0, -10.0, -8.0, -6.0, -4.0, -2.0, -0.0 Data Sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVAnd analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.4, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is 0.01 degrees. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. Signal to noise ratio was fixed to 1. Logarithmic transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. The weight of time series was decreased by a factor of 10 relative to the weight of the profiles to account for the redundancy in the time series observations. Detrending of data: no, Advection constraint applied: no. Units: umol/l.

In the framework of the ANR AMORAD project, the METEOR cruises (Grasso, 2017) aimed at deploying the ‘Gironde Estuary Mouth MEasurement Stations’ (GEMMES) to measure hydrodynamics and sediment dynamics at the mouth of the Gironde Estuary and on the West Gironde Mud Patch (SW France, Bay of Biscay). Measurements were carried out between November 2016 and December 2017: i) from a buoy station around 20-m water depth (GEMMES-20), collecting sub-surface data of temperature, salinity and turbidity; and ii) a benthic station around 40-m water depth (GEMMES-40), collecting data of current velocity and turbidity. Bottom and surface water samples were regularly collected to calibrate turbidity measurements to SPM concentrations.

Satellite altimeters routinely supply sea surface height (SSH) measurements which are key observations to monitor ocean dynamics. However, below a wavelength of about 70 km, along-track altimeter measurements are often characterized by a dramatic drop in the signal-to-noise ratio, making it very challenging to fully exploit available altimeter observations to precisely analyze small mesoscale variations in SSH. Although various approaches have been proposed and applied to identify and filter noise from measurements, no distinctive methodology emerged to be systematically applied in operational products. To best cope with this unresolved issue, the Copernicus Marine Environment Monitoring Service (CMEMS) actually provides simple band-pass filtered data to mitigate noise contamination in the along-track SSH signals and more innovative and adapted noise filtering methods are thus left to users seeking to unveil small-scale altimeter signals. Here demonstrated, a fully data-driven approach is developed and applied to provide robust estimates of noise-free Sea Level Anomaly (SLA) signals. The method combines Empirical Mode Decomposition (EMD), to help analyze non-stationary and non-linear processes, and an adaptive noise filtering technique inspired by Discrete Wavelet Transform (DWT) decompositions. It is now found to best resolve the distribution of the sea surface height variability in the mesoscale 30-120 km wavelength band. A practical uncertainty variable is attached to the denoised SLA estimates that accounts for errors related to the local signal to noise ratio, but also for uncertainties in the denoising process, which assumes that SLA variability results in part from a stochastic process. Here, measurements from the Jason-3, Sentinel-3 A and SARAL/AltiKa altimeters are processed and analyzed, and their energy spectral and seasonal distributions characterized in the small mesoscale domain. Anticipating data from the upcoming Surface Water and Ocean Topography (SWOT) mission, these denoised SLA measurements for three reference altimeter missions already yield valuable opportunities to assess global small mesoscale kinetic energy distributions. This dataset was developed within the Ocean Surface Topography Science Team (OSTST) activities. A grant was awarded to the SASSA (Satellite Altimeter Short-scale Signals Analysis) project by the TOSCA board in the framework of the CNES/EUMETSAT call CNES-DSP/OT 12-2118. Altimeter data were provided by the Copernicus Marine Environment Monitoring Service (CMEMS) and by the Sea State Climate Change Initiative (CCI) project.

Moving 6-year analysis of Water_body_dissolved_inorganic_nitrogen_(DIN) in the Mediterranean Sea for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centered average of the season. 6-years periods span from 1990-1995 until 2014-2019. Observational data span from 1970 to 2019. Depth range (IODE standard depths): -1100.0, -1000.0, -900.0, -800.0, -700.0, -600.0, -500.0, -400.0, -300.0, -250.0, -200.0, -150.0, -125.0, -100.0, -75.0, -50.0, -30.0, -20.0, -10.0, -5.0, -0.0. Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVA (Data-Interpolating Variational Analysis) tool. Profiles were interpolated at standard depths using weighted parabolic interpolation algorithm (Reiniger and Ross, 1968). GEBCO 1min topography is used for the contouring preparation. Analysed filed masked using relative error threshold 0.3 and 0.5. DIVA settings: A constant value for signal-to-noise ratio was used equal to 1. Correlation length was optimized and filtered vertically and a seasonally-averaged profile was used. 'log(data)-exp(analysis' transformation applied to the data prior to the analysis. Background field: the data mean value is subtracted from the data. Detrending of data: no. Advection constraint applied: no. Units: umol/l. The entire set of related maps can be found in the viewing service: http://ec.oceanbrowser.net/emodnet/ . Originators of Italian data sets-List of contributors: - Brunetti Fabio (OGS) - Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306 - Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987 - Cataletto Bruno (OGS) - Cinzia Comici Cinzia (OGS) - Civitarese Giuseppe (OGS) - DeVittor Cinzia (OGS) - Giani Michele (OGS) - Kovacevic Vedrana (OGS) - Mosetti Renzo (OGS) - Solidoro C.,Beran A.,Cataletto B.,Celussi M.,Cibic T.,Comici C.,Del Negro P.,De Vittor C.,Minocci M.,Monti M.,Fabbro C.,Falconi C.,Franzo A.,Libralato S.,Lipizer M.,Negussanti J.S.,Russel H.,Valli G., doi:10.6092/e5518899-b914-43b0-8139-023718aa63f5 - Celio Massimo (ARPA FVG) - Malaguti Antonella (ENEA) - Fonda Umani Serena (UNITS) - Bignami Francesco (ISAC/CNR) - Boldrini Alfredo (ISMAR/CNR) - Marini Mauro (ISMAR/CNR) - Miserocchi Stefano (ISMAR/CNR) - Zaccone Renata (IAMC/CNR) - Lavezza, R., Dubroca, L. F. C., Ludicone, D., Kress, N., Herut, B., Civitarese, G., Cruzado, A., Lefèvre, D., Souvermezoglou, E., Yilmaz, A., Tugrul, S., and Ribera d'Alcala, M.: Compilation of quality controlled nutrient profiles from the Mediterranean Sea, doi:10.1594/PANGAEA.771907, 2011.

The West Gironde Mud Patch (WGMP) is a 420-km2 mud belt in the Bay of Biscay, located 25 km off the mouth of the Gironde estuary. This clay-silt feature of 4 m in thickness extends between 30 and 75m water depth, surrounded by the sands and gravels that cover the North Aquitaine continental shelf. Interface cores were collected during JERICOBent-1 cruise (October 2016; Deflandre (2016) doi.org/10.17600/16010400) along two cross-shelf transects for a total of 9 sites. Each sediment core was carefully extruded every 0.5 cm from the top core to 4 cm and every 1 cm below until the core bottom. The sediment layers were used to determine dry bulk density, grain size and selected radioisotope activities (210Pb, 226Ra, 137Cs, 228Th, K).

This map presents all layers corresponding to "Sea and coastal freight water transport" activities in the Atlantic area. For more information about this NACE code : https://ec.europa.eu/eurostat/ramon/nomenclatures/index.cfm?TargetUrl=DSP_NOM_DTL_VIEW&StrNom=NACE_REV2&StrLanguageCode=EN&IntPcKey=18512804&IntKey=18512894&StrLayoutCode=HIERARCHIC&IntCurrentPage=1 Indicators collected are : Business indicators per country Number of persons employed and number of employees in full time equivalent units per NUTS 3 unit of the Atlantic Area Overall passenger traffic per main Atlantic port

This visualization product displays the total abundance of marine macro-litter (> 2.5cm) per beach per year from Marine Strategy Framework Directive (MSFD) monitoring surveys. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of beach litter have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols and reference lists used on a European scale. Preliminary processing were necessary to harmonize all the data: - Exclusion of OSPAR 1000 protocol: in order to follow the approach of OSPAR that it is not including these data anymore in the monitoring; - Selection of MSFD surveys only (exclusion of other monitoring, cleaning and research operations); - Exclusion of beaches without coordinates; - Some categories & some litter types like organic litter, small fragments (paraffin and wax; items > 2.5cm) and pollutants have been removed. The list of selected items is attached to this metadata. This list was created using EU Marine Beach Litter Baselines and EU Threshold Value for Macro Litter on Coastlines from JRC (these two documents are attached to this metadata); - Normalization of survey lengths to 100m & 1 survey / year: in some cases, the survey length was not exactly 100m, so in order to be able to compare the abundance of litter from different beaches a normalization is applied using this formula: Number of items (normalized by 100 m) = Number of litter per items x (100 / survey length) Then, this normalized number of items is summed to obtain the total normalized number of litter for each survey. Finally, the median abundance for each beach and year is calculated from these normalized abundances per survey. Sometimes the survey length was null or equal to 0. Assuming that the MSFD protocol has been applied, the length has been set at 100m in these cases. Percentiles 50, 75, 95 & 99 have been calculated taking into account MSFD data for all years. More information is available in the attached documents. Warning: the absence of data on the map doesn't necessarily mean that it doesn't exist, but that no information has been entered in the Marine Litter Database for this area.

This visualization product displays plastic bags density per trawl. EMODnet Chemistry included the collection of marine litter in its 3rd phase. Since the beginning of 2018, data of seafloor litter collected by international fish-trawl surveys have been gathered and processed in the EMODnet Chemistry Marine Litter Database (MLDB). The harmonization of all the data has been the most challenging task considering the heterogeneity of the data sources, sampling protocols (OSPAR and MEDITS protocols) and reference lists used on a European scale. Moreover, within the same protocol, different gear types are deployed during fishing bottom trawl surveys. In cases where the wingspread and/or number of items were unknown, data could not be used because these fields are needed to calculate the density. Data collected before 2011 are affected by this filter. When the distance reported in the data was null, it was calculated from: - the ground speed and the haul duration using this formula: Distance (km) = Haul duration (h) * Ground speed (km/h); - the trawl coordinates if the ground speed and the haul duration were not filled in. The swept area is calculated from the wingspread (which depends on the fishing gear type) and the distance trawled: Swept area (km²) = Distance (km) * Wingspread (km) Densities have been calculated on each trawl and year using the following computation: Density of plastic bags (number of items per km²) = ∑Number of plastic bags related items / Swept area (km²) Percentiles 50, 75, 95 & 99 have been calculated taking into account data for all years. The list of selected items for this product is attached to this metadata. Information on data processing and calculation is detailed in the attached methodology document. Warning: the absence of data on the map doesn't necessarily mean that they don't exist, but that no information has been entered in the Marine Litter Database for this area.